Predictive Index for Long-Term Survival After Retransplantation of the Liver in Adult Recipients: Analysis of a 26-Year Experience in a Single Center.

MedLine Citation:

PMID:
21817890
Owner:
NLM
Status:
Publisher

Abstract/OtherAbstract:

OBJECTIVE:: To develop a prognostic scoring system for risk stratification of patients with hepatic graft failure (GF) undergoing retransplants of the liver (ReLT) and improve patient selection. SUMMARY OF BACKGROUND DATA:: Retransplantation of the liver remains controversial because of inferior outcomes compared with the primary orthotopic liver transplantation (OLT) and raises concerns of inappropriate utilization of a scarce donor organ resource. Data on risk stratification of ReLT patients for long-term survival outcomes are limited. METHODS:: We conducted an analysis from our prospective database of 466 adults' ReLT between February 1984 and September 2010. Mean follow-up was 3 years. Each independent predictor for allograft failure was assigned risk score (RS) points of 1 or 2, proportional to the corresponding parameter estimate under the Cox model: Predictive index category (PIC) 1, RS = 0; PIC II, RS = 1 to 2; PIC III, RS = 3 to 4; and PIC IV, RS = 5 to 12. RESULTS:: Eight risk factors predictive for GF after ReLT included recipient age greater than 55 years, Model for End-Stage Liver Disease score greater than 27, history of prior OLT greater than 1, pre-ReLT requirement for mechanical ventilation, serum albumin less than 2.5 g/dL, donor age greater than 45 years, intraoperative requirement of packed red blood cell transfusion greater than 30 units, and performance of ReLT between 15 and 180 days from the prior OLT. Five-year GF-free survival was significantly higher in PIC I (65%) than in PIC II (53%), PIC III (43%), and PIC IV (20%) groups (P < 0.001). CONCLUSIONS:: This risk-stratification model was highly predictive of long-term outcome after liver retransplantation in adult recipients. This formula provides a practical guide for selection of candidates for retransplantation of the liver that can lead to improved patient outcomes and optimal utilization of a scarce resource.

*Dumont-UCLA Transplant and Liver Cancer Centers, Pfleger Liver Institute, Department of Surgery †Department of Biomathematics, David Geffen School of Medicine at University of California, Los Angeles.